The Problem: How to add more granularity to digital out-of-home campaign planning
As the out-of-home advertising ecosystem has evolved from billboard ads to digital screens, brands have started to see the medium in a different light. And now that they’ve started to see the tremendous value in being able to tap into a wealth of data and insights to plan, target, buy, execute, and measure out-of-home advertising campaigns, they want to get even more granular with their planning.
Over the last few years, Adomni has been getting more requests from brands and advertisers to reach highly targeted digital out-of-home (DOOH) audiences using location-based data. The only problem is that getting access to clean, accurate, and up-to-date POI data that can fuel this kind of targeting is not always a quick and easy task. In many cases, Adomni’s team had to rely on the advertisers themselves to supply whatever POI data they had to work with or try to build it themselves via public data sources.
Either way, sourcing this data became a major sticking point for a number of reasons. First, the datasets were oftentimes inaccurate or incomplete—especially at the brand- or category-level. Second, sometimes it took too long to get access to the right datasets, which slowed down campaign planning significantly. And lastly, when an advertiser wanted to do competitive conquesting, in many cases there was simply no reliable data to work with at all. So it soon became abundantly clear that in order to address this growing demand from brands and advertisers to plan DOOH campaigns with a POI-based strategy, Adomni needed access to high-quality geospatial data at nationwide scale.
The Problem-Solver: Adomni
Adomni was founded to give brands and advertisers a new way to buy ad space on digital out-of-home screens through an easy-to-use online marketplace with transparent pricing, advanced audience targeting capabilities, screen-level metrics for detailed forecasting and budgeting, and most importantly, the ability to launch campaigns in a matter of minutes.
Today, they’ve more than delivered on this mission. At the time of this case study, their cutting-edge and highly visual DOOH platform aggregates 700k+ screens, across 40+ countries, 40 venue types (i.e. bars, restaurants, airports, malls, etc.), and 350 publishers—delivering 70B impressions monthly (and growing).
What sets Adomni apart from other multichannel programmatic platforms is their core focus on innovating the digital out-of-home advertising space. Not to mention, their world-class managed services team includes some of the industry’s leading DOOH experts who seek to help brands and advertisers tap into the full potential of the digital out-of-home advertising space.
Our customers expect to be able to build highly-targeted digital out-of-home campaigns fueled by location data; we simply couldn’t have made this a reality—at massive scale–without partnering with SafeGraph.
The Solution: SafeGraph Places
To make granular targeting based on POI data a perennial reality, Adomni looked no further than the SafeGraph Places dataset. “Building POI-based campaign planning strategies in an ad hoc way with inconsistent data was not a scalable long-term solution for addressing our customers’ evolving needs,” said Nicholas Babb, SVP of Product at Adomni. “We needed access to reliable, high-quality POI data with massive nationwide coverage in order to scale our audience targeting capabilities in the way that our customers needed us to do it.”
Making the choice to work with SafeGraph ended up being a rather easy decision for Adomni’s team. Babb continued, “Their data quality was the decision-maker for us—and only SafeGraph passed our ‘sniff test’ after we had a chance to vet and validate their data.” All in all, three things about SafeGraph really stood out during their evaluation of potential data partners:
- The sheer size of the SafeGraph Places dataset, covering millions of POIs in the U.S.;
- The freshness (and accuracy) of the dataset thanks to monthly updates; and
- The usefulness of the dataset’s taxonomy, especially around brand and category tags.
“While we were convinced that the quality and scale of SafeGraph’s data was exactly what we needed to enhance our platform’s capabilities, their team’s willingness and desire to be a great partner has not gone by unnoticed,” reiterated Babb. “Everyone at SafeGraph has been really supportive from the very beginning and always quick to respond whenever we’ve needed help.”
The Result: Delivering more effective digital out-of-home campaigns with POI data
“Thanks to SafeGraph, we’ve now been able to make it possible for our customers to use our self-service tools to build a campaign strategy around POI data within a matter of seconds,” explained Babb. This is a big departure from the past when manually sourcing location data to fuel campaign planning could sometimes take days–if not weeks–to find, share, clean, and upload relevant datasets that were cobbled together from various sources. “Even better, as the SafeGraph Places dataset evolves, grows, and becomes even more robust each month, we and our customers benefit from it,” concluded Babb.
